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WHAT YOU DO AT AMD CHANGES EVERYTHING At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. The Role We are seeking a highly skilled Data Scientist to lead initiatives in advanced analytics, predictive modeling, and generative AI for our Sales Operations org. This role combines statistical expertise, machine learning, and cutting-edge generative models to deliver actionable insights that drive strategic decisions across multiple business areas. As part of our team, you will collaborate with cross-functional teams to optimize revenue, improve operations, and empower sales and marketing professionals by leveraging data-driven solutions and AI to minimize manual tasks, enabling them to focus more efficiently on selling products. The Person The person we are looking for should have passion in data science. He/she has strong SQL and programming skills (Python is preferred) and has a good understanding of statistics and machine learning algorithms. Key Responsibilities Predictive Modeling & Machine Learning: Develop and deploy predictive models using machine learning algorithms (e.g., XGBoost, Random Forest) to address business challenges such as customer segmentation and revenue forecast. Build end-to-end ML pipelines from data ingestion to model deployment, ensuring scalability and reliability. Time-Series Forecasting: Create robust time-series forecasting models for revenue, demand, and operational metrics using techniques like ARIMA, Prophet, Bayesian methods, and hybrid approaches. Partner with finance, sales, and operations teams to integrate forecasts into strategic planning and decision-making processes. Generative AI & Advanced Analytics: Design and implement generative AI solutions (e.g., LLMs, GANs) for business applications such as information retrieval, workflow automation, and AI-driven decision systems. Data Pipeline & Infrastructure Collaborate with data engineering teams to design and maintain scalable data pipelines using tools like Airflow, KNIME, or custom shell scripting. Leverage big data frameworks (e.g., Snowflake, Hadoop, Spark) for efficient data processing and storage. Exploratory Data Analysis & Visualization: Perform exploratory data analysis to uncover patterns and insights from structured and unstructured data sources. Develop visualizations using tools such as Plotly, Matplotlib and Seaborn to communicate findings effectively to stakeholders. Collaboration & Impact Measurement: Work closely with business leaders, data engineers, and BI teams to align on business needs and deliver impactful solutions. Monitor model performance post-deployment and iterate on models to ensure continued business impact. Continuous Learning & Innovation: Stay updated on emerging technologies in AI, machine learning, and generative models. Experiment with new tools and techniques to enhance team capabilities and drive innovation. Qualifications Education: Bachelor’s degree (Master’s preferred) in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field. Technical Skills: Proficiency in Python, SQL, and other programming languages. Strong understanding of machine learning algorithms and statistical techniques. Hands-on experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and frameworks for generative AI. Familiarity with time-series forecasting methods and tools. Experience working with big data technologies (e.g., Snowflake, Hadoop, Spark). Basic knowledge of UNIX shell scripting (Bash, Zsh). Experience: Minimum of 3+ years of experience in data science or related fields. Demonstrated ability to deliver end-to-end ML projects from start to finish. Experience with version control tools like Git and GitHub. Business Acumen: Ability to translate technical insights into actionable business strategies. Strong communication skills to effectively collaborate with cross-functional teams. This role is not eligible for visa sponsorship. LOCATION: Austin, TX AMD does not accept unsolicited resumes from headhunters, recruitment agencies or fee based recruitment services. AMD and its subsidiaries are equal opportunity employers and will consider all applicants without regard to race, marital status, sex, age, color, religion, national origin, veteran status, disability or any other characteristic protected by law. EOE/MFDV Benefits offered are described: AMD benefits at a glance. AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process. AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here. This posting is for an existing vacancy.
Most are in India and the US. Here's how to pick the right one for you.
74.689Jobs
17.483IN
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WorkMundi's database shows 74,689 open sales positions globally. India leads with 17,483 jobs, followed by the US with 13,876. If you're open to geography, you have real options — but the sheer number means you need a filter. Don't apply to everything. Pick a country, a company size, and a sales model that matches what you actually want to do.
Almost 8 in 10 of these ads have their text written in English. That's useful for reading the job description and understanding what you're signing up for. But it tells you nothing about whether the role requires you to speak English with customers, partners, or your team. Ask the hiring manager directly during your first conversation.
The employers posting the most are boxlunch, SIMPLE RECRUIT, FlexBoard, and tmobile. If you see their name on a listing, you know they're actively hiring. That can work in your favor — high-volume recruiters often move faster. But volume also means competition. Your application needs to stand out.
Sales interviews almost always include a version of this: 'Tell me about a time you lost a deal. What did you learn?' Prepare a real story where you take ownership of what went wrong and what you'd do differently. Hiring managers want to see you learn, not just win.